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Record W4392238644 · doi:10.1017/s0008423923000707

When a “Feminist” Government Tackles Gender-Based Violence: A WPR Approach to the Speeches of Canadian Cabinet Ministers (2015–2019)

2024· article· en· W4392238644 on OpenAlexaffabout
Bailey Gerrits

Bibliographic record

VenueCanadian Journal of Political Science · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicGender Politics and Representation
Canadian institutionsUniversity of WinnipegSt. Francis Xavier University
FundersUniversity of Cambridge
KeywordsCabinet (room)Government (linguistics)Political scienceGender studiesSociologyArtVisual artsPhilosophyLinguistics

Abstract

fetched live from OpenAlex

Abstract Ending gender-based violence was a central promise of Prime Minister Justin Trudeau's self-declared feminist government. Executive speeches about gender-based violence provide clues about what types of feminist ideas undergird the 42nd Parliament. Was carceral feminism advanced, by focusing on punishment? Or neoliberalized feminist ideas, by focusing on the market? Or social justice feminist ideas, by focusing on systemic change? Applying the concept of governance feminism and using Bacchi's WPR approach, this article investigates how gender-based violence is problematized in English- and French-language House of Commons debates in the 42nd Parliament by the cabinet. The speeches problematize gender-based violence as preventable and caused by systemic issues, but this transformational discourse is undermined by a focus on strengthening carceral responses and limiting human potential to economic productivity. Feminist ideas about gender-based violence were adopted, relying on carceral and neoliberalized feminist ideas. The Trudeau Liberals’ campaign for change was discursively undermined.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.892
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.054
GPT teacher head0.316
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2024
Admission routes2
Has abstractyes

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